def test_adaptive_splitting_3d_3():
# adaptively refine one face of a cube, check that the mesh parameter h
# is approximately linear w.r.t to distance from the face
m = MeshTet.init_tensor(np.linspace(0, 1, 3), np.linspace(0, 1, 3),
np.linspace(0, 1, 3))
for itr in range(15):
m = m.refined(m.f2t[0, m.facets_satisfying(lambda x: x[0] == 0)])
@LinearForm
def hproj(v, w):
return w.h * v
basis = Basis(m, ElementTetP1())
h = projection(hproj, basis)
funh = basis.interpolator(h)
xs = np.vstack((
np.linspace(0, .5, 20),
np.zeros(20) + .5,
np.zeros(20) + .5,
))
hs = funh(xs)
assert np.max(np.abs(hs - xs[0])) < 0.063
def test_adaptive_splitting_3d_4():
# check that the same mesh is reproduced by any future versions
m = MeshTet.init_tensor(np.linspace(0, 1, 2), np.linspace(0, 1, 2),
np.linspace(0, 1, 2))
m = m.refined(m.f2t[0, m.facets_satisfying(lambda x: x[0] == 0)])
assert_array_equal(
m.p,
np.array([[0., 0., 1., 1., 0., 0., 1., 1., 0.5],
[0., 1., 0., 1., 0., 1., 0., 1., 0.5],
[0., 0., 0., 0., 1., 1., 1., 1., 0.5]]))
assert_array_equal(
m.t,
np.array([[5, 3, 3, 5, 6, 6, 1, 4, 1, 2, 2, 4],
[0, 0, 0, 0, 0, 0, 7, 7, 7, 7, 7, 7],
[1, 1, 2, 4, 2, 4, 5, 5, 3, 3, 6, 6],
[8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8]]))
